Work on the DevOps team, building robust continuous integration (CI) tests to deliver quality software faster through continuous deployment (CD). The team is responsible for building and maintaining a wide variety of apps, internal tools, and infrastructures, requiring familiarity with an equally wide variety of programming languages (Python, SQL, Bash, Java, Groovy, etc.) and skillsets (designing, building, testing, maintaining software).

This project aims to understand the increase in intensity and frequency of extreme weather in recent decades. The hypothesis is that human-driven climate change is weakening the temperature gradient from the equator to the pole, causing the jet-stream to meander. However, this hypothesis is difficult to test without a tool capable of identifying and measuring peaks in troughs in the meandering jet-stream. This tool is precisely what this time is hoping to develop. We are working in Python and using data from NOAA which extends back to the 80s. We are trying various approaches to try to train an AI to identify points at which the jet-stream meanders (called peaks and troughs). The team is international and very multidisciplinary.

The goal of the research is to understand the air pollution levels in Kathmandu, Nepal. I am tasked with writing a program capable of interpreting, doing calculations on, and running analyses on millions of radiosonde data points efficiently. I'm working in Python with a few modules such as Numpy, Datetime, and OS. After the gathering, parsing, cand cleaning of the data, the output values of interest are put into an SQL database using the SQLite module. We are testing artificial neural network (ANN) approaches in order to investigate the links between numerous atmospheric parameters derived from the radiosonde data and particulate matter levels in Kathmandu.